Device, system, and method of creating virtual social networks based on web-extracted features

ABSTRACT

Device, system, and method of creating virtual social networks based on web-extracted features. For example, a method for creating virtual social networks based on web-extracted data includes: accessing through a global communication network a first content item and a second content item, wherein each one of the first and second content items is selected from the group consisting of: an image, a video, text, and metadata; extracting data corresponding to a first feature from the first content item; extracting data corresponding to a second feature from the second content item; and based on a common attribute of the first and second features, clustering into a cluster a first identifier of a first user associated with the first content item and a second identifier of a second user associated with the second content item.

FIELD

Some embodiments of the invention are related to the field of electroniccommunication systems able to provide virtual social network services.

BACKGROUND

Some electronic communication systems allow users to create or join avirtual community, as well as to engage in virtual social networkservices. For example, some Internet web-sites (e.g., “MySpace.com” or“Facebook.com”) provide a collection of various ways for users tointeract. User interactions include, for example, online chatactivities, instant messaging, sharing of photographs and videos, filesharing, writing into a “blog” system or reading from a “blog” system,or the like.

Some systems allow a user to import or reuse his contact list orelectronic mail (email) address book, and to utilize such contacts oremail addresses for creation of a virtual social network. This mechanismallows the user to create a virtual social network which includespersons that the user already knows, but may not allow the user tocreate a virtual social network with persons that the user does not yetknow.

SUMMARY

Some embodiments include, for example, devices, systems, and methods ofcreating virtual social networks based on web-extracted features.

In some embodiments, for example, a method for creating virtual socialnetworks based on web-extracted data includes: accessing through aglobal communication network a first content item and a second contentitem, wherein each one of the first and second content items is selectedfrom the group consisting of: an image, a video, text, and metadata;extracting data corresponding to a first feature from the first contentitem; extracting data corresponding to a second feature from the secondcontent item; and based on a common attribute of the first and secondfeatures, clustering into a cluster a first identifier of a first userassociated with the first content item and a second identifier of asecond user associated with the second content item.

In some embodiments, for example, an apparatus for creating virtualsocial networks based on web-extracted data includes: a crawler moduleto access through a global communication network a first content itemand a second content item, wherein each one of the first and secondcontent items is selected from the group consisting of: an image, avideo, text, and metadata; one or more content analyzers to extract datacorresponding to a first feature from the first content item, and toextract data corresponding to a second feature from the second contentitem; and a clustering module to cluster into a cluster, based on acommon attribute of the first and second features, a first identifier ofa first user associated with the first content item and a secondidentifier of a second user associated with the second content item.

Some embodiments may include, for example, a computer program productincluding a computer-useable medium including a computer-readableprogram, wherein the computer-readable program when executed on acomputer causes the computer to perform methods in accordance with someembodiments of the invention.

Some embodiments may provide other and/or additional benefits and/oradvantages.

BRIEF DESCRIPTION OF THE DRAWINGS

For simplicity and clarity of illustration, elements shown in thefigures have not necessarily been drawn to scale. For example, thedimensions of some of the elements may be exaggerated relative to otherelements for clarity of presentation. Furthermore, reference numeralsmay be repeated among the figures to indicate corresponding or analogouselements. The figures are listed below.

FIG. 1 is a schematic block diagram illustration of a system inaccordance with some demonstrative embodiments of the invention.

FIG. 2 is a schematic flow-chart of a method of creating virtual socialnetworks based on web-extracted features, in accordance with somedemonstrative embodiments of the invention.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are setforth in order to provide a thorough understanding of some embodimentsof the invention. However, it will be understood by persons of ordinaryskill in the art that embodiments of the invention may be practicedwithout these specific details. In other instances, well-known methods,procedures, components, units and/or circuits have not been described indetail so as not to obscure the discussion.

Discussions herein utilizing terms such as, for example, “processing,”“computing,” “calculating,” “determining,” “establishing”, “analyzing”,“checking”, or the like, may refer to operation(s) and/or process(es) ofa computer, a computing platform, a computing system, or otherelectronic computing device, that manipulate and/or transform datarepresented as physical (e.g., electronic) quantities within thecomputer's registers and/or memories into other data similarlyrepresented as physical quantities within the computer's registersand/or memories or other information storage medium that may storeinstructions to perform operations and/or processes.

The terms “plurality” and “a plurality” as used herein include, forexample, “multiple” or “two or more”. For example, “a plurality ofitems” includes two or more items.

Although portions of the discussion herein relate, for demonstrativepurposes, to wired links and/or wired communications, embodiments of theinvention are not limited in this regard, and may include one or morewired or wireless links, may utilize one or more components of wirelesscommunication, may utilize one or more methods or protocols of wirelesscommunication, or the like. Some embodiments of the invention mayutilize wired communication and/or wireless communication.

Some embodiments may be used in conjunction with various devices andsystems, for example, a Personal Computer (PC), a desktop computer, amobile computer, a laptop computer, a notebook computer, a tabletcomputer, a server computer, a handheld computer, a handheld device, aPersonal Digital Assistant (PDA) device, a handheld PDA device, anon-board device, an off-board device, a hybrid device (e.g., a deviceincorporating functionalities of multiple types of devices, for example,PDA functionality and cellular phone functionality), a vehicular device,a non-vehicular device, a mobile or portable device, a non-mobile ornon-portable device, a wireless communication station, a wirelesscommunication device, a wireless Access Point (AP), a wireless BaseStation (BS), a Mobile Subscriber Station (MSS), a wired or wirelessNetwork Interface Card (NIC), a wired or wireless router, a wired orwireless modem, a wired or wireless network, a Local Area Network (LAN),a Wireless LAN (WLAN), a Metropolitan Area Network (MAN), a Wireless MAN(WMAN), a Wide Area Network (WAN), a Wireless WAN (WWAN), a PersonalArea Network (PAN), a Wireless PAN (WPAN), devices and/or networksoperating in accordance with existing IEEE 802.11, 802.11a, 802.11b,802.11g, 802.11n, 802.16, 802.16d, 802.16e, 802.16m standards and/orfuture versions and/or derivatives and/or Long Term Evolution (LTE) ofthe above standards, units and/or devices which are part of the abovenetworks, one way and/or two-way radio communication systems, cellularradio-telephone communication systems, a cellular telephone, a wirelesstelephone, a Personal Communication Systems (PCS) device, a PDA devicewhich incorporates a wireless communication device, a mobile or portableGlobal Positioning System (GPS) device, a device which incorporates aGPS receiver or transceiver or chip, a device which incorporates an RFIDelement or tag or transponder, a device which utilizes Near-FieldCommunication (NFC), a Multiple Input Multiple Output (MIMO) transceiveror device, a Single Input Multiple Output (SIMO) transceiver or device,a Multiple Input Single Output (MISO) transceiver or device, a devicehaving one or more internal antennas and/or external antennas, a wiredor wireless handheld device (e.g., BlackBerry, Palm Treo), a WirelessApplication Protocol (WAP) device, or the like.

Some embodiments may be used in conjunction with one or more types ofwireless communication signals and/or systems, for example, RadioFrequency (RF), Infra Red (IR), Frequency-Division Multiplexing (FDM),Orthogonal FDM (OFDM), OFDM Access (OFDMA), Time-Division Multiplexing(TDM), Time-Division Multiple Access (TDMA), Extended TDMA (E-TDMA),General Packet Radio Service (GPRS), extended GPRS, Code-DivisionMultiple Access (CDMA), Wideband CDMA (WCDMA), CDMA 2000, Multi-CarrierModulation (MDM), Discrete Multi-Tone (DMT), Bluetooth®, GlobalPositioning System (GPS), IEEE 802.11 (“Wi-Fi”), IEEE 802.16 (“Wi-Max”),ZigBee™, Ultra-Wideband (UWB), Global System for Mobile communication(GSM), 2 G, 2.5 G, 3 G, Third Generation Partnership Project (3GPP), 3.5G, or the like. Some embodiments may be used in conjunction with variousother devices, systems and/or networks.

The term “wireless device” as used herein includes, for example, adevice capable of wireless communication, a communication device capableof wireless communication, a communication station capable of wirelesscommunication, a desktop computer capable of wireless communication, amobile phone, a cellular phone, a laptop or notebook computer capable ofwireless communication, a PDA capable of wireless communication, ahandheld device capable of wireless communication, a portable ornon-portable device capable of wireless communication, or the like.

The terms “social network” or “virtual social network” or “VSN” as usedherein include, for example, a virtual community, an online community, acommunity or assembly of online representations corresponding to usersof computing devices, a community or assembly of virtual representationscorresponding to users of computing devices, a community or assembly ofvirtual entities (e.g., avatars, usernames, nicknames, or the like)corresponding to users of computing devices, or the like.

In some embodiments, a virtual social network includes at least twousers; in other embodiments, a virtual social network includes at leastthree users. In some embodiments, a virtual social network includes atleast one “one-to-many” communication channels or links. In someembodiments, a virtual social network includes at least onecommunication channel or link that is not a point-to-point communicationchannel or link. In some embodiments, a virtual social network includesat least one communication channel or link that is not a “one-to-one”communication channel or link.

The terms “social network services” or “virtual social network services”as used herein include, for example, one or more services which may beprovided to members or users of a social network, e.g., through theInternet, through wired or wireless communication, through electronicdevices, through wireless devices, through a web-site, through astand-alone application, through a web browser application, or the like.In some embodiments, social network services may include, for example,online chat activities; textual chat; voice chat; video chat; InstantMessaging (IM); non-instant messaging (e.g., in which messages areaccumulated into an “inbox” of a recipient user); sharing of photographsand videos; file sharing; writing into a “blog” or forum system; readingfrom a “blog” or forum system; discussion groups; electronic mail(email); folksonomy activities (e.g., tagging, collaborative tagging,social classification, social tagging, social indexing); forums; messageboards; or the like.

The terms “web” or “Web” as used herein includes, for example, the WorldWide Web; a global communication system of interlinked and/or hypertextdocuments, files, web-sites and/or web-pages accessible and/or publiclyavailable through the Internet or through a global communicationnetwork; including text, images, videos, multimedia components,hyperlinks, or other content.

At an overview, some embodiments include devices, systems, and methodsof creating virtual social networks based on web-extracted personalfeatures. For example, a web crawler crawls the World Wide Web, anddownloads text, images, videos, blog postings, personal web-pages, orthe like. The crawled content is analyzed by one or more analyzers, forexample, an image analyzer, a video analyzer, a text analyzer, and/or ametadata analyzer, which extract personal features from the crawledcontent. A clustering module creates a cluster of users who publishedonline content having a common attribute.

For example, the image analyzer determines that an online image wastaken in London; the video analyzer determines that an online video wastaken in London; the text analyzer determines that a blog postingrelates to a visit in London; the metadata analyzer determines that anonline content items is associated with London; or the like.Accordingly, the clustering module creates a cluster of users associatedwith London. Similarly, a cluster may include a group of users whopossess a common article, who visited a common landmark, who showedinterest in a common hobby, or the like.

The generated clusters may be used in order to generate virtual socialnetworks. For example, the system may send to users of a particularcluster invitations to join a virtual social network associated with thecommon attribute of the cluster. Additionally or alternatively, theclusters may be used in order to selectively send commercial content tousers that are members of a particular clusters. For example, based onthe common attribute of the cluster, a merchant platform may send to themembers of the cluster relevant advertisements, promotions, orcommercial offers.

The term “personal features” as used herein includes, for example,features or data extracted by an analysis of web-content uploaded,published, or otherwise shared or made publicly available online by auser of the World Wide Web or of other global communication network.Although portions of the discussion herein relate, for demonstrativepurposes, to extraction and utilization of personal features, someembodiments may extract and/or utilize data or features which may notnecessarily be “personal” in their nature, for example, business-relateddata, web-content uploaded or published or shared by a business entity,web-content uploaded or published or shared by a group of users or by afamily, or the like.

FIG. 1 schematically illustrates a block diagram of a system 100 inaccordance with some demonstrative embodiments of the invention. System100 includes multiple client devices, for example, devices 101-104.Devices 101-104 may include wired computing devices and/or wirelesscomputing devices. For example, device 101 may be a desktop computerhaving a cable modem 111; device 102 may be a laptop computer having anIEEE 802.16 transceiver 112; device 103 may be a cellular phone having acellular transceiver 113; and device 104 may be a PDA device having anIEEE 802.11 transceiver 114. Each one of devices 101-104 is able toaccess the World Wide Web (“Web”) 190 through the Internet globalcommunication network, using wired and/or wireless communication links191-194.

System 100 further includes a server 120 implemented using suitablehardware components and/or software components, for example, a processor121, an input unit 122, an output unit 123, a memory unit 124, a storageunit 125, and a communication unit 126.

Processor 121 includes, for example, a Central Processing Unit (CPU), aDigital Signal Processor (DSP), one or more processor cores, asingle-core processor, a dual-core processor, a multiple-core processor,a microprocessor, a host processor, a controller, a plurality ofprocessors or controllers, a chip, a microchip, one or more circuits,circuitry, a logic unit, an Integrated Circuit (IC), anApplication-Specific IC (ASIC), or other suitable multi-purpose orspecific processor or controller. Processor 121 executes instructions,for example, of an Operating System (OS) 127 or of one or moreapplications 128.

Input unit 122 includes, for example, a keyboard, a keypad, a mouse, atouch-pad, a joystick, a track-ball, a stylus, a microphone, or othersuitable pointing unit or input device. Output unit 123 includes, forexample, a monitor, a screen, a Cathode Ray Tube (CRT) display unit, aLiquid Crystal Display (LCD) display unit, a plasma display unit, one ormore audio speakers or earphones, or other suitable output devices.

Memory unit 124 includes, for example, a Random Access Memory (RAM), aRead Only Memory (ROM), a Dynamic RAM (DRAM), a Synchronous DRAM(SD-RAM), a flash memory, a volatile memory, a non-volatile memory, acache memory, a buffer, a short term memory unit, a long term memoryunit, or other suitable memory units. Storage unit 125 includes, forexample, a hard disk drive, a floppy disk drive, a Compact Disk (CD)drive, a CD-ROM drive, a Digital Versatile Disk (DVD) drive, an internalor external database or repository, or other suitable removable ornon-removable storage units. Memory unit 124 and/or storage unit 125,for example, store data processed by server 120.

Communication unit 126 includes, for example, a wired or wirelesstransceiver, a wired or wireless modem, a wired or wireless NetworkInterface Card (NIC), or other unit suitable for transmitting and/orreceiving communication signals, blocks, frames, transmission streams,packets, messages and/or data. Optionally, communication unit 126includes, or is associated with, one or more antennas. In someembodiments, communication unit 126 allows server 120 to access the Web,for example, through a wired or wireless communication link 195.

In some embodiments, some or all of the components of server 120 areenclosed in a common housing or packaging, and are interconnected oroperably associated using one or more wired or wireless links. In otherembodiments, components of server 120 are distributed among multiple orseparate devices or locations.

A first user utilizes the device 101 in order to post online, to submitonline, to share, to upload, or to otherwise publish online an image181. The image 181 may be, for example, a photograph, a drawing, anoriginal image, a scanned image, a file representing or includinggraphics or graphical element(s), or the like. In a demonstrativeexample, image 181 includes a photograph of the first user holding aSprite bottle. Optionally, the filename of image 181 includes the string“Sprite”. Optionally, when publishing or sharing the image 181, thefirst user provides his email address or other contact detail, forexample, “User1@domain.com”.

A second user utilizes the device 102 in order to post online, to submitonline, to share, to upload, or to otherwise publish online a video 182.The video 182 may be, for example, a file having digital datarepresenting a moving picture, a set or sequence of images, a streamingvideo, a non-streaming video, a video which optionally includes an audiotrack, an encoded or non-encoded video, an audio/video file utilizingone or more compression schemes or encoding schemes for encoding orcompression of audio and/or video, or the like. In a demonstrativeexample, video 182 is a two-minute audio/video file, which includes afive-seconds portion showing the second user and the Statue of Libertyin the background. Optionally, the video file is Optionally video 182 ispublished online with a filename “Statue_of_Liberty.jpg” (e.g., afilename determined by the second user prior to uploading the videofile); and/or with an “alt” tag or title of “My trip to the Statue ofLiberty”. When publishing or sharing the video 182, the second userprovides his email address or other contact detail, for example,“User2@domain.com”.

A third user utilizes the device 103 in order to post online, to submitonline, to share, to upload, or to otherwise publish online a web-log(“blog”) posting 183. The blog posting 183 may be, for example, anoriginal or new posting, a response to a previous posting, a textualposting, a posting which includes text and other objects (e.g., images,videos, a signature), a posting into a forum or a threaded mechanism, a“talk-back” posting, a comment to an online article, a comment to anonline posting, or the like. In a demonstrative example, the blogposting 183 is a textual posting which includes the phrase “I enjoydrinking Sprite”. Optionally, when publishing or sharing the blogposting 183, the third user provides his email address or other contactdetail, for example, “User3@domain.com”.

A fourth user utilizes the device 104 in order to post online, to submitonline, to share, to upload, or to otherwise publish online otherpersonal content, for example, a personal web-page 184. The personalweb-page 184 may be, for example, a personal web-site, one or morehosted web-pages, a portion of a web-page, a user profile posted onto avirtual social network, or the like. In a demonstrative example, thepersonal web-page 184 may include the phrase “Last month I visited NewYork City, saw the Statue of Liberty, and bought a red shirt”.Optionally, when publishing or sharing the personal web-page 184, thefourth user provides his email address or other contact detail, forexample, “User4@domain.com”.

Server 120 includes a web crawler 170, for example, a web “spider” or“ant”, a web robot or “bot”, an automatic indexer, a program or softwareagent or automated script able to browse the Web 190 in a methodical orautomated manner. Web crawler 170 may be able to systematically copyand/or index web-sites and/or web-pages, to automatically gatherinformation from web-sites and/or web-pages, and/or to automaticallycrawl or browser the Web 190 based on one or more “seed” UniformResource Locators (URLs) and based on hyperlinks in previously-crawledweb-pages. Web crawler 170 may include multiple or distributed agents,and may include multiple sub-unites, for example, a multi-threadedweb-paged downloader, a scheduler, a queue manager, or the like.

Web crawler 170 is able to download and obtain from the Web 190 data,for example, text, images, videos, blog postings, rich content, or thelike; as well as metadata, namely, data about data, e.g., a filename ofan image file, a filename of a video file, an “alt” tag of an image(namely, text that is rendered or displayed instead of or in addition toa graphical element). The data and metadata downloaded by web crawler170 is optionally stored (e.g., cached, stored for short-term storage,or stored for long-term storage) in a crawled information repository175.

Server 120 includes one or more analysis modules and/or featureextractors able to analyze the information stored in the crawledinformation repository 175, or able to analyze crawled information insubstantially real time (e.g., without long-term storage of the crawledinformation in the crawled information repository 175). For example, animager analyzer 171 is able to analyze images crawled from the Web 190;a video analyzer 172 is able to analyze videos crawled from the Web 190;a text analyzer is able to analyze textual content crawled from the Web190; and a metadata analyzer is able to analyze metadata crawled fromthe Web 190. Analyzers 171-174 may extract personal features 187 fromthe crawled information, and may store the extracted personal features187 in an extracted features repository 176. The personal features 187may include one or more types of web-extracted data, or data extractedfrom web-content that one or more users publish, upload, or otherwiseshare using the Web 190 or another global communication network.

For example, the web crawler 170 crawls the Web 190 and downloads theimage 181 published by the user of device 101. The image analyzer 171analyzes the image 181, and identifies the bottle of “Sprite” (or thelogo of “Sprite”) therein. Accordingly, the image analyzer 171 stores inthe extracted features repository 176 a first record indicating that acontact detail of the user of device 101 (e.g., his email address,“User1@domain.com”, which is obtained by the web crawler 170) isassociated with the word “Sprite”, with the word “bottle”, and with theterm “red shirt” (e.g., if image 181 shows the first user wearing a redshirt).

Similarly, the web crawler 170 crawls the Web 190 and downloads thevideo 182 published by the user of device 102. The video analyzer 172analyzes the video 182, and identifies the Statue of Liberty therein.Accordingly, the video analyzer 172 stores in the extracted featuresrepository 176 a second record indicating that a contact detail of theuser of device 102 (e.g., his email address, “User2@domain.com”, whichis obtained by the web crawler 170) is associated with the term “Statueof Liberty”.

Furthermore, the web crawler 170 crawls the Web 190 and downloads theblog posting 183 published by the user of device 103. The text analyzer173 analyzes the blog posting 182, and identifies the phrase “I enjoydrinking Sprite” therein. Accordingly, the text analyzer 173 stores inthe extracted features repository 176 a third record indicating that acontact detail of the user of device 103 (e.g., his email address,“User3@domain.com”, which is obtained by the web crawler 170) isassociated with the word “Sprite”.

Additionally, the web crawler 170 crawls the Web 190 and downloads thepersonal web-page 184 published by the user of device 104. The textanalyzer 173 analyzes the personal web-page 184, and identifies the term“Statue of Liberty” and the term “red shirt”. Accordingly, the textanalyzer 173 stores in the extracted features repository 176 a fourthrecord indicating that a contact detail of the user of device 104 (e.g.,his email address, “User4@domain.com”, which is obtained by the webcrawler 170) is associated with the term “Statue of Liberty” and withthe term “red shirt”.

Furthermore, the web crawler 170 crawls the Web 190 and downloads thevideo 182 published by the user of device 102. The metadata analyzer 174analyzes metadata associated with the video 182, and identifies thefilename “Statue_of_Liberty.jpg” and/or the title “My trip to the Statueof Liberty”. Accordingly, the metadata analyzer 174 stores in theextracted features repository 176 a fifth record indicating that acontact detail of the user of device 102 (e.g., his email address,“User2@domain.com”, which is obtained by the web crawler 170) isassociated with the term “New York City”.

Server 120 further includes a clustering module 177 able to performclassification, partitioning, matching, or other types of grouping ofmultiple records stored in the extracted features repository 176 intoone or more groups or clusters, such that members in each cluster sharea common attribute or characteristic. For example, the clustering module177 may create a first cluster, in which the first user and the thirduser (or their corresponding contact details or email addresses) aremembers, since both of these users are associated with the word“Sprite”. Similarly, the clustering module 177 may create a secondcluster, in which the first user and the fourth user (or theircorresponding contact details or email addresses) are members, sinceboth of these users are associated with the term “red shirt”. Similarly,the clustering module 177 may create a third cluster, in which thesecond user and the fourth user (or their corresponding contact detailsor email addresses) are members, since both of these users areassociated with the term “Statue of Liberty”. Information representingthe clustering of records into clusters may be added by the clusteringmodule to the extracted features repository 176 (e.g., by adding datainto additional field(s) in suitable records); or may be storedseparately, for example, in a linked list or a clusters repository 188.

Server 120 may create and may operate virtual social network(s) based onthe information, namely, based on personal features 187 extracted fromcrawled web-pages and crawled web-content and clustered by theclustering module 177. An invitation module 178 may send an invitation(e.g., by email) to members of a cluster, inviting them to join avirtual social network associated with the common attribute of thecluster. For example, the invitation module 178 may selectively sendinvitations to the first and third users (and not to the second andfourth users), inviting them to join a virtual social network of userswho like to drink “Sprite” or showed a common interest in “Sprite”.Similarly, the invitation module 178 may selectively send invitations tothe second and fourth users (and not to the first and third users),inviting them to join a virtual social network of users who visited theStatue of Liberty or showed a common interest in the Statue of Liberty.

Upon reception of the invitation, a user may utilize the correspondingdevice (101-104) to accept the invitation or to reject the invitation.If the user accepts the invitation, an identifier of the user (e.g., hisemail address, his contact detail, or a user-entered identifier ornickname) is added to a participants table 197 of the virtual socialnetwork. If the user rejected the invitation, he is not added to theparticipants table 197 of the virtual social network. The user'sresponse is transferred back to the invitation module 178 of server 120.

Upon reception of at least one acceptance of invitation, a virtualsocial network generator 180 generates or creates a virtual socialnetwork associated with the common attribute of the relevant cluster;and virtual social network services 161 are provided to users that areincluded in the participants table 179 of that virtual social network.The virtual social network services 181 are provided, for example, usingan application server 162, a web server 163, middleware 164, or othersuitable components.

Optionally, clustered information (e.g., clusters of web-extractedpersonal features) may be transferred to third parties or to externalplatforms, for example, a vendor or merchant platform 185, which may beassociated with a commercial content module 186 able to providecommercial content based on cluster attributes. For example, a clusterof web-extracted personal features may be transferred from theclustering module 177 or from the clustering repository 188 to themerchant platform 185, indicating that the first and third users (ortheir corresponding contact details or email addresses) are interestedin “Sprite”; accordingly, the commercial content module 186 mayselectively transfer to these users advertisements, promotions,discounts, coupons, or special offers related to “Sprite” (e.g., adiscount coupon for purchasing a “Sprite” bottle, or a discount couponfor purchasing particular brands of soft drinks).

Similarly, for example, a cluster of web-extracted personal features maybe transferred from the clustering module 177 or from the clusteringrepository 188 to the merchant platform 185, indicating that the secondand fourth users (or their corresponding contact details or emailaddresses) are interested in “Statue of Liberty”; accordingly, thecommercial content module 186 may selectively transfer to these usersadvertisements, promotions, discounts, coupons, or special offersrelated to “Statue of Liberty” (e.g., an advertisement to purchase abook about the history of the Statue of Liberty, or an offer to purchasea miniature replica of the Statue of Liberty).

In some embodiments, image analyzer 171 and/or video analyzer 172 mayutilize one or more suitable algorithms for image analysis or videoanalysis. In some embodiments, imager analyzer 171 and/or video analyzer172 may utilize facial recognition algorithms, for example, eigenfacealgorithm, fisherface algorithm, Hidden Markov model, dynamic linkmatching, or the like. In some embodiments, visual searching algorithmsmay be used, for example, similar to algorithms used by visual searchengines (e.g., “www.LIKE.com”, “www.RIYA.com”). Some embodiments mayutilize algorithms to identify objects and features in images and videosusing one or more methods described in U.S. Pat. No. 5,640,468 to Hsu,issued on Jun. 17, 1997, titled “Method for Identifying Objects andFeatures in an Image”. In some embodiments, video analysis may include,for example, image analysis of one or more frames of the video.

In some embodiments, image analyzer 171 and/or video analyzer 172 mayutilize one or more algorithms adapted to determine a location in whicha photograph was taken, algorithms adapted to determine a commonlandmark or item which appears in multiple images or videos, oralgorithms adapted to derive from a photograph a geo-spatial data (e.g.,geo-spatial coordinates) of the location in which the photograph wastaken, for example, geo-tagging algorithms, GPS-tagging algorithms, oneor more methods described online in MAKE magazine by Phillip Torrone onJul. 3, 2005 at“http://blog.makezine.com/archive/2005/07/how_to_gps_tag.html”.

Some embodiments may thus utilize personal data obtained by crawling theWeb 190, for example, the content of pictures or videos that userspublish online (e.g., in Flickr, Phanfare, or other services), contentof blogs, personal pages in Facebook, or the like, in order to create avirtual social network based on a common interest or attribute. Someembodiments may create a virtual social network by crawling the contentof existing social networks and additional online sources, for example,online images, online videos, blogs, personal web-pages, or the like.Some embodiments may create a virtual social network not necessarily by(or not exclusively by) explicitly merging social graphs of existingvirtual social networks and online services, but rather, may createvirtual social networks by crawling and analyzing data from the Web 190.

Some embodiments may utilize feature extraction from pictures or videos,as well as content analysis algorithms, in order to identify users whoshare one or more common attributes. The common attributes may be, forexample, common places that people visited, common articles that peoplepossess, or the like. Users that share one or more common attributes maybe clustered together. Based on the generated clusters, some embodimentsmay suggest to users to purchase items or services, based on featuresand personal data extracted from online content; and optionally takinginto account historical purchases made by users.

In some embodiments, for example, once a cluster of users associatedwith “New York City” is identified, the merchant platform 185 may offerto users of the cluster trips to New York City, trips to otherdestinations (e.g., London) which visitors to New York City may enjoy,offers to purchase books about New York City, offers to purchase NewYork City souvenirs or memorabilia, or the like.

In some embodiments, for example, a cluster of users associated with theterm “Harry Potter” may be identified based on analysis of onlineimages, based on analysis of online videos, based on analysis of blogpostings or personal web-pages, based on analysis of metadata (e.g.,“alt” tag, file names), or the like. Once the cluster is identified, themerchant platform may send to some or all members of the clusterselected offers or content, for example, an offer to purchase “HarryPotter” related items or memorabilia (e.g., shirt, cup, toy, or thelike), an offer to purchase books or movies that fans of Harry Pottermay enjoy, or the like.

In some embodiments, the clustering module 177 may generate a clusterhaving more than one common attribute, for example, if clusters having asingle common attribute have a number of possible members greater than athreshold value. For example, a cluster associated with “New York City”may be associated with 51,000 users; a cluster associated with “Sprite”may be associated with 62,000 users; and a cluster associated with “redshirt” may be associated with 48,000 users; whereas a cluster associatedwith the three terms together may be associated with only 300 members,and may provide an improved user experience to some users who prefer toparticipate in smaller virtual social networks.

In some embodiments, the clustering module 177 may generate a clusterbased on one or more features extracted from one or more images; and/orone or more features extracted from one or more videos; and/or one ormore features extracted from one or more web-pages, personal web-pages,or blog postings; and/or one or more features extracted from one or moremetadata items. In some embodiments, at least one of the extractedfeatures that the clustering module takes into account may be anon-textual item or a non-text, for example, an image or a video.

Although portions of the discussion herein relate, for demonstrativepurposes, to analysis of images and videos, and to extraction ofpersonal features from images and videos, some embodiments may utilizeanalysis of other rich-content items or extraction of features fromother rich-content items, for example, multimedia items, Flash items,Shockwave items, or the like.

Some embodiments may utilize a client/server architecture, apublisher/subscriber architecture, a centralized architecture, ascalable Peer-to-Peer (P2P) architecture, a fully distributedarchitecture, a semi-distributed or partially-distributed architecture,or other suitable architectures or combinations thereof.

FIG. 2 is schematic flow-chart of a method of creating virtual socialnetworks based on web-extracted features, in accordance with somedemonstrative embodiments of the invention. Operations of the method maybe used, for example, by system 100 of FIG. 1, and/or by other suitableunits, devices and/or systems.

In some embodiments, the method may include, for example, crawling theWeb and downloading Web content (block 210), e.g., data and/or metadata.

In some embodiments, the method may include, for example, extractingpersonal features from crawled Web content (block 220).

In some embodiments, the method may include, for example, clusteringextracted personal features based on one or more common attributes(block 230).

In some embodiments, the method may include, for example, generating avirtual social network associated with the one or more common attributes(block 240). This may include, for example, sending invitations tomembers of the cluster to join the virtual social network; receivingacceptance(s) to join the virtual social network; adding the acceptingusers to a list of participants of the virtual social network; andproviding virtual social network services to the participants of thevirtual social network.

In some embodiments, the method may include, for example, selectivelyproviding tailored commercial content to one or more members of thecluster based on the one or more common attributes (block 250).

In some embodiments, the operation of block 250 may be performed insteadof, or in addition to, the operation of block 240. Other suitableoperations or sets of operations may be used in accordance withembodiments of the invention.

Some embodiments of the invention, for example, may take the form of anentirely hardware embodiment, an entirely software embodiment, or anembodiment including both hardware and software elements. Someembodiments may be implemented in software, which includes but is notlimited to firmware, resident software, microcode, or the like.

Furthermore, some embodiments of the invention may take the form of acomputer program product accessible from a computer-usable orcomputer-readable medium providing program code for use by or inconnection with a computer or any instruction execution system. Forexample, a computer-usable or computer-readable medium may be or mayinclude any apparatus that can contain, store, communicate, propagate,or transport the program for use by or in connection with theinstruction execution system, apparatus, or device.

In some embodiments, the medium may be an electronic, magnetic, optical,electromagnetic, infrared, or semiconductor system (or apparatus ordevice) or a propagation medium. Some demonstrative examples of acomputer-readable medium may include a semiconductor or solid statememory, magnetic tape, a removable computer diskette, a random accessmemory (RAM), a read-only memory (ROM), a rigid magnetic disk, and anoptical disk. Some demonstrative examples of optical disks includecompact disk-read only memory (CD-ROM), compact disk-read/write(CD-R/W), and DVD.

In some embodiments, a data processing system suitable for storingand/or executing program code may include at least one processor coupleddirectly or indirectly to memory elements, for example, through a systembus. The memory elements may include, for example, local memory employedduring actual execution of the program code, bulk storage, and cachememories which may provide temporary storage of at least some programcode in order to reduce the number of times code must be retrieved frombulk storage during execution.

In some embodiments, input/output or I/O devices (including but notlimited to keyboards, displays, pointing devices, etc.) may be coupledto the system either directly or through intervening I/O controllers. Insome embodiments, network adapters may be coupled to the system toenable the data processing system to become coupled to other dataprocessing systems or remote printers or storage devices, for example,through intervening private or public networks. In some embodiments,modems, cable modems and Ethernet cards are demonstrative examples oftypes of network adapters. Other suitable components may be used.

Functions, operations, components and/or features described herein withreference to one or more embodiments, may be combined with, or may beutilized in combination with, one or more other functions, operations,components and/or features described herein with reference to one ormore other embodiments, or vice versa.

While certain features of some embodiments of the invention have beenillustrated and described herein, many modifications, substitutions,changes, and equivalents may occur to those skilled in the art. It is,therefore, to be understood that the appended claims are intended tocover all such modifications and changes.

1. A method for creating virtual social networks based on web-extracteddata, the method comprising: searching through content published in awide area distributed communication network for identifiers identifyingrespective publishers of said content, wherein said identifiers areutilized to contact the publisher of said content, if the content isselected for inclusion in a content index in a virtual social network,and wherein the searching process is triggered independent of a keywordsearch initiated by an individual that is identifiable by a particularsearch engine used to perform the keyword search; determining a firstidentifier associated with a first content item and a second identifierassociated with a second content item, wherein each one of the first andsecond content items comprises one or more of an image, a video, text,and metadata, or a combination thereof; extracting data corresponding toa first feature from the first content item; extracting datacorresponding to a second feature from the second content item;recognizing a common attribute that is common to the first and secondfeatures; and associating the first identifier and the second identifiersuch that the publishers of the first content and the second content areindexed into a common group based on the common attribute recognized forthe first and the second features.
 2. The method of claim 1, wherein thesearching through content published in a wide area distributedcommunication network comprises: automatically browsing the World WideWeb using a crawling algorithm.
 3. The method of claim 1, furthercomprising: identifying a representation included in the first andsecond content items, wherein the representation is selected from one ormore of: a representation of a common landmark, a representation of acommon person, or a representation of a common article.
 4. The method ofclaim 1, wherein at least one of the first and second content items is anon-text content item from which data corresponding to the commonattribute is extracted using algorithms for at least one of imagerecognition, text recognition, geo-spatial data recognition, orgeo-tagging.
 5. The method of claim 1, comprising: sending to thepublishers of the first content and the second content invitations tojoin a virtual social network associated with the common attribute ofthe first and second features, wherein said invitations are sent to theidentifiers identifying the respective publishers of said content,wherein said identifiers are utilized to contact the publisher of saidcontent, if the content is selected for inclusion in a content indexthat is to be publically shared among members of the virtual socialnetwork, and wherein the invitations are submitted by an automatedsystem rather than by an affirmative action taken by an existing memberof the virtual social network.
 6. The method of claim 5, comprising:receiving a signal indicating user acceptance of the invitation; andadding the user to the virtual social network associated with the commonattribute of the first and second features.
 7. The method of claim 6,comprising: providing one or more virtual social network services to oneor more participants of the virtual social network.
 8. The method ofclaim 1, comprising: sending to at least one of the first and secondusers a commercial content item based on the common attribute of thefirst and second features.
 9. The method of claim 8, wherein thecommercial content item is selected from the group consisting of: anadvertisement, a promotion, a coupon, a discount representation, anoffer to purchase an item, an offer to purchase a service, an offer toreceive a free item, and an offer to receive a free service.
 10. Anapparatus for creating virtual social networks based on web-extracteddata, the apparatus comprising: a crawler module for searching throughcontent published in a wide area distributed communication network foridentifiers identifying respective publishers of said content, whereinsaid identifiers are utilized to contact the publisher of said content,if the content is selected for inclusion in a content index, and whereinthe searching process is triggered independent of a keyword searchinitiated by an individual that is identifiable by a particular searchengine used to perform the keyword search; one or more content analyzersfor determining a first identifier associated with a first content itemand a second identifier associated with a second content item, whereineach one of the first and second content items comprises one or more ofan image, a video, text, and metadata, or a combination thereof;extracting data corresponding to a first feature from the first contentitem; extracting data corresponding to a second feature from the secondcontent item; recognizing a common attribute of the first and secondfeatures; and a clustering module for associating the first identifierand the second identifier such that the publishers of the first contentand the second content are indexed into a common group based on thecommon attribute recognized for the first and the second features. 11.The apparatus of claim 10, wherein at least one of the first and secondcontent items is a non-text content item from which data correspondingto a common feature is extracted using algorithms for at least one ofimage recognition, text recognition, geo-spatial data recognition, orgeo-tagging.
 12. The apparatus of claim 10, wherein the crawler moduleis to automatically browse the World Wide Web using a crawlingalgorithm.
 13. The apparatus of claim 10, wherein the one or morecontent analyzers are to identify one or more representations selectedfrom the group consisting of: a representation of a common landmarkincluded in the first and second content items; a representation of acommon person included in the first and second content items; and arepresentation of a common article included in the first and secondcontent items.
 14. The apparatus of claim 10, comprising: an invitationmodule for sending to the publishers of the first content and the secondcontent invitations to join a virtual social network associated with thecommon attribute of the first and second features, wherein saidinvitations are sent to the identifiers identifying the respectivepublishers of said content, wherein said identifiers are utilized tocontact the publisher of said content, if the content is selected forinclusion in a content index that is to be publically shared amongmembers of the virtual social network, and wherein the invitations aresubmitted by an automated system rather than by an affirmative actiontaken by an existing member of the virtual social network.
 15. Theapparatus of claim 14, wherein the invitation module is to receive asignal indicating user acceptance of the invitation, and wherein theapparatus comprises a virtual social network generator to add the userto the virtual social network associated with the common attribute ofthe first and second features.
 16. The apparatus of claim 15, whereinthe virtual social network generator is to provide one or more virtualsocial network services to one or more participants of the virtualsocial network.
 17. The apparatus of claim 10, comprising: a commercialcontent platform to send to at least one of the first and second users acommercial content item based on the common attribute of the first andsecond features.
 18. The apparatus of claim 17, wherein the commercialcontent item is selected from the group consisting of: an advertisement,a promotion, a coupon, a discount representation, an offer to purchasean item, an offer to purchase a service, an offer to receive a freeitem, and an offer to receive a free service.
 19. A computer programproduct comprising a tangible computer readable storage medium includinga computer readable program, wherein the computer readable program whenexecuted on a computer causes the computer to: search through contentpublished in a wide area distributed communication network foridentifiers identifying respective publishers of said content, whereinsaid identifiers are utilized to contact the publisher of said content,if the content is selected for inclusion in a content index, and whereinthe searching process is triggered independent of a keyword searchinitiated by an individual that is identifiable by a particular searchengine used to perform the keyword search; determine a first identifierassociated with a first content item and a second identifier associatedwith a second content item, wherein each one of the first and secondcontent items comprises one or more of an image, a video, text, andmetadata, or a combination thereof; extract data corresponding to afirst feature from the first content item; extract data corresponding toa second feature from the second content item; recognize a commonattribute of the first and second features; and associate the firstidentifier and the second identifier such that the publishers of thefirst content and the second content are indexed into a common groupbased on the common attribute recognized for the first and the secondfeatures.
 20. The computer program product of claim 19, wherein thecomputer readable program when executed on the computer further causesthe computer to: identify one or more representations comprising one ormore of: a representation of a common landmark included in the first andsecond content items; a representation of a common person included inthe first and second content items; or a representation of a commonarticle included in the first and second content items.